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Examines the association between functional disability and depressive symptoms in older people. Analysis of the reciprocal effects between depressive symptoms and functional disability; Link between disability and depressive symptoms; Treatment for improving the quality of life of elderly.

Parental psychopathology, parenting style, and the quality of intrafamilial relationships are all associated with child mental health outcomes. However, most research can say little about the causal pathways underlying these associations. This is because most studies are not genetically informative and are therefore not able to account for the possibility that associations are confounded by gene-environment correlation. That is, biological parents not only provide a rearing environment for their child, but also contribute 50% of their genes. Any associations between parental phenotype and child phenotype are therefore potentially confounded. One technique for disentangling genetic from environmental effects is the children-of-twins (COT) method. This involves using data sets comprising twin parents and their children to distinguish genetic from environmental associations between parent and child phenotypes. The COT technique has grown in popularity in the last decade, and we predict that this surge in popularity will continue. In the present article we explain the COT method for those unfamiliar with its use. We present the logic underlying this approach, discuss strengths and weaknesses, and highlight important methodological considerations for researchers interested in the COT method. We also cover variations on basic COT approaches, including the extended-COT method, capable of distinguishing forms of gene-environment correlation. We then present a systematic review of all the behavioral COT studies published to date. These studies cover such diverse phenotypes as psychosis, substance abuse, internalizing, externalizing, parenting, and marital difficulties. In reviewing this literature, we highlight past applications, identify emergent patterns, and suggest avenues for future research. [ABSTRACT FROM AUTHOR]

Background: Positive, negative and disorganised psychotic symptom dimensions are associated with clinical and developmental variables, but differing definitions complicate interpretation. Additionally, some variables have had little investigation., Aims: To investigate associations of psychotic symptom dimensions with clinical and developmental variables, and familial aggregation of symptom dimensions, in multiple samples employing the same definitions., Method: We investigated associations between lifetime symptom dimensions and clinical and developmental variables in two twin and two general psychosis samples. Dimension symptom scores and most other variables were from the Operational Criteria Checklist. We used logistic regression in generalised linear mixed models for combined sample analysis ( n = 875 probands). We also investigated correlations of dimensions within monozygotic (MZ) twin pairs concordant for psychosis ( n = 96 pairs)., Results: Higher symptom scores on all three dimensions were associated with poor premorbid social adjustment, never marrying/cohabiting and earlier age at onset, and with a chronic course, most strongly for the negative dimension. The positive dimension was also associated with Black and minority ethnicity and lifetime cannabis use; the negative dimension with male gender; and the disorganised dimension with gradual onset, lower premorbid IQ and substantial within twin-pair correlation. In secondary analysis, disorganised symptoms in MZ twin probands were associated with lower premorbid IQ in their co-twins., Conclusions: These results confirm associations that dimensions share in common and strengthen the evidence for distinct associations of co-occurring positive symptoms with ethnic minority status, negative symptoms with male gender and disorganised symptoms with substantial familial influences, which may overlap with influences on premorbid IQ.

Background: Previous research indicates that body dysmorphic disorder (BDD) is associated with risk of suicidality. However, studies have relied on small and/or specialist samples and largely focussed on adults, despite these difficulties commonly emerging in youth. Furthermore, the aetiology of the relationship remains unknown., Methods: Two independent twin samples were identified through the Child and Adolescent Twin Study in Sweden, at ages 18 (N = 6027) and 24 (N = 3454). Participants completed a self-report measure of BDD symptom severity. Young people and parents completed items assessing suicidal ideation/behaviours. Logistic regression models tested the association of suicidality outcomes with: (a) probable BDD, classified using an empirically derived cut-off; and (b) continuous scores of BDD symptoms. Bivariate genetic models examined the aetiology of the association between BDD symptoms and suicidality at both ages., Results: Suicidal ideation and behaviours were common among those with probable BDD at both ages. BDD symptoms, measured continuously, were linked with all aspects of suicidality, and associations generally remained significant after adjusting for depressive and anxiety symptoms. Genetic factors accounted for most of the covariance between BDD symptoms and suicidality (72.9 and 77.7% at ages 18 and 24, respectively), but with significant non-shared environmental influences (27.1 and 22.3% at ages 18 and 24, respectively)., Conclusions: BDD symptoms are associated with a substantial risk of suicidal ideation and behaviours in late adolescence and early adulthood. This relationship is largely explained by common genetic liability, but non-shared environmental effects are also significant and could provide opportunities for prevention among those at high-risk.

Individual differences in cognitive ability and social behaviour are influenced by the variability in the structure and function of the limbic system. A strong heritability of the limbic cortex has been previously reported, but little is known about how genetic factors influence specific limbic networks. We used diffusion tensor imaging tractography to investigate heritability of different limbic tracts in 52 monozygotic and 34 dizygotic healthy adult twins. We explored the connections that contribute to the activity of three distinct functional limbic networks, namely the dorsal cingulum ('medial default-mode network'), the ventral cingulum and the fornix ('hippocampal-diencephalic-retrosplenial network') and the uncinate fasciculus ('temporo-amygdala-orbitofrontal network'). Genetic and environmental variances were mapped for multiple tract-specific measures that reflect different aspects of the underlying anatomy. We report the highest heritability for the uncinate fasciculus, a tract that underpins emotion processing, semantic cognition, and social behaviour. High to moderate genetic and shared environmental effects were found for pathways important for social behaviour and memory, for example, fornix, dorsal and ventral cingulum. These findings indicate that within the limbic system inheritance of specific traits may rely on the anatomy of distinct networks and is higher for fronto-temporal pathways dedicated to complex social behaviour and emotional processing., (© The Author (2015). Published by Oxford University Press.)

The classical twin study is the most popular design in behavioural genetics. It has strong roots in biometrical genetic theory, which allows predictions to be made about the correlations between observed traits of identical and fraternal twins in terms of underlying genetic and environmental components. One can infer the relative importance of these 'latent' factors (model parameters) by structural equation modelling (SEM) of observed covariances of both twin types. SEM programs estimate model parameters by minimising a goodness-of-fit function between observed and predicted covariance matrices, usually by the maximum-likelihood criterion. Likelihood ratio statistics also allow the comparison of fit of different competing models. The program Mx, specifically developed to model genetically sensitive data, is now widely used in twin analyses. The flexibility of Mx allows the modelling of multivariate data to examine the genetic and environmental relations between two or more phenotypes and the modelling to categorical traits under liability-threshold models.